Cosma / Communication / Content / Data
You can use all the quantitative data you can get, but you still have to distrust it and use your own intelligence and judgment. — Alvin Toffler
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Introduction1
University of Guelph McLaughlin Library (YouTube Channel)
Working with Data (University of Guelph McLaughlin Library)
Dictionary
data : factual information (such as measurements or statistics) used as a basis for reasoning, discussion, or calculation — Merriam-Webster See also OneLook
Thesaurus
Roget’s II (Thesaurus.com), Merriam-Webster Thesaurus, Visuwords
Encyclopedia
Data are units of information, often numeric, that are collected through observation. In a more technical sense, data are a set of values of qualitative or quantitative variables about one or more persons or objects, while a datum (singular of data) is a single value of a single variable. Although the terms “data” and “information” are often used interchangeably, these terms have distinct meanings. Data are sometimes said to be transformed into information when they are viewed in context or in post-analysis. — Wikipedia
Data (Encyclopædia Britannica)
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I never guess. It is a capital mistake to theorize before one has data. Insensibly one begins to twist facts to suit theories, instead of theories to suit facts. — Sir Arthur Conan Doyle, The Sign of Four, A Scandal in Bohemia
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Inspiration
TEDxTalks (YouTube Channel)
TEDx Program (Official Website)
Making Data Mean More Through Storytelling (Ben Wellington, TEDxBroadway)
Talks about Data (TED: Ideas Worth Spreading)
Articles about Data (Big Think)
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Foundation
System
Data system is a term used to refer to an organized collection of symbols and processes that may be used to operate on such symbols. Any organized collection of symbols and symbol-manipulating operations can be considered a data system. A data system is defined in terms of some data model and bears a resemblance to the idea of a physical symbol system. — Wikipedia
What Is a Data System, Anyway? (Peter Cornillon, EDUCAUSE Review)
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Innovation
Big Data deals with ways to analyze, systematically extract information from, or otherwise deal with data sets that are too large or complex to be dealt with by traditional data-processing application software. Data with many fields (columns) offer greater statistical power, while data with higher complexity (more attributes or columns) may lead to a higher false discovery rate. Big data analysis challenges include capturing data, data storage, data analysis, search, sharing, transfer, visualization, querying, updating, information privacy, and data source. — Wikipedia
Simplilearn (YouTube Channel)
Big Data Career Guide (Nikita Duggal, Simplilearn)
Big Data: The Next Frontier for Innovation, Competition, and Productivity (James Manyika, et al., McKinsey & Company)
Big Data (IEEE)
Science
Data science uses scientific methods, processes, algorithms and systems to extract knowledge and insights from structured and unstructured data,and apply knowledge and actionable insights from data across a broad range of application domains. Data science is related to data mining, machine learning and big data. It uses techniques and theories drawn from many fields within the context of mathematics, statistics, computer science, information science, and domain knowledge. — Wikipedia
Data Science Tutorial (Simplilearn, YouTube Playlist)
Big Data Career Guide (Nikita Duggal, Simplilearn)
What is Data Science? (UC Berkeley School of Information)
Technology
See Spreadsheet and Database
Commerce
Entrepreneurship
Data Campaigns (Kickstarter)
Data Campaigns (Indiegogo)
Product
Data Gifts (Zazzle)
Data (Etsy)
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Preservation
History
Intro to Data Science (Steve Brunton, YouTube Playlist)
The Fourth Paradigm (Tony Hey, et al., Microsoft)
Data-Driven Science and Engineering (Steven L. Brunton & J. Nathan Kutz)
Steve Brunton’s Lab: Data-Driven Dynamics and Control (Website)
Data Systems (Engineering and Technology History Wiki)
Beginner’s Guide to the History of Data Science (Hannah Augur, Dataconomy)
Museum
The Museum of Data (UCL Anthropology Department)
Library
DDC: 005.7 Data (Library Thing)
Subject: Data (Library Thing)
LCC: QA 76.9 Data (UPenn Online Books)
Subject: Data (UPenn Online Books)
LCC: QA 76.9 Data (Library of Congress)
Subject: Data (Library of Congress)
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Participation
Education
MERLOT: Multimedia Educational Resource for Learning and Online Teaching
OER Commons: Open Educational Resources
Course
Analyzing/Presenting Data/Information Course (Edward Tufte)
Edward Tufte (YouTube Channel)
Edward Tufte (Official Website)
The Visual Display of Quantitative Information (Edward Tufte)
Envisioning Information (Edward Tufte)
Visual Explanations: Images and Quantities, Evidence and Narrative (Edward Tufte)
Beautiful Evidence (Edward Tufte)
Data Science: Visualization (HarvardX)
Data Science: Inference and Modeling (HarvardX)
Principles, Statistical and Computational Tools for Reproducible Data Science (HarvardX)
Data Science Certificate Program (HarvardX)
Community
Occupation
CareerOneStop, YouTube Channel (U.S. Department of Labor, Employment and Training Administration)
CareerOneStop, Official Website (U.S. Department of Labor, Employment and Training Administration)
CareerOneStop, YouTube Channel (U.S. Department of Labor, Employment and Training Administration)
CareerOneStop, Official Website (U.S. Department of Labor, Employment and Training Administration)
Data Scientists (CareerOneStop, U.S. Department of Labor, Employment and Training Administration)
3 Data Careers Decoded and What It Means for You (Cheng Han Lee, Udacity)
Big Data Career Guide: A Comprehensive Playbook To Becoming A Big Data Engineer (Nikita Duggal, Simplilearn)
Organization
Special Interest Group on Management of Data (SIGMOD, ACM)
Special Interest Group on Knowledge Discovery and Data Mining (SIGKDD, ACM)
Harvard Data Science Initiative (Harvard University)
Institute for Data, Systems & Society (Massachusetts Institute of Technology)
News
ACM SIGMOD Record
ACM SIGKDD Explorations Newsletter
Data (JSTOR)
Data (NPR Archives)
Government
Document
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Expression
Arts
Art Made of Data Playlist (TED Talks)
Poem
The DIKW pyramid, also known variously as the DIKW hierarchy, wisdom hierarchy, knowledge hierarchy, information hierarchy, information pyramid, and the data pyramid, refers loosely to a class of models for representing purported structural and/or functional relationships between the communication content types of data, information, knowledge, and wisdom. — Wikipedia
Most writers about the hierarchy refer to this passage from T. S. Eliot’s The Rock.
Where is the Life we have lost in living?
Where is the wisdom we have lost in knowledge?
Where is the knowledge we have lost in information? — T. S. Eliot, The Rock
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These are links to pages about closely related subjects.
DIKW Content Hierarchy
Data, Information, Knowledge and Wisdom
See also Spreadsheet and Database
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1. The resources on this page are are organized by a classification scheme developed exclusively for Cosma.